GEO series

Single-cell profiling across treatment stages enables precision targeting of therapy-resistant neuroblastoma

GSE331214 Homo sapiens (human) Single-cell RNA-seq 38 samples Submitted 2026/10/08 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 38 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 38 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.

Summary (written by the submitters)

Minor drug-resistant populations emerge during treatment in cancers such as neuroblastoma and later drive relapse. There are no reliable methods for tracking or molecularly defining the cells that escape therapy or tailored therapeutic strategies to eradicate them. We generated longitudinal single cell transcriptomes of tumour tissues taken at diagnosis (Dx), at delayed tumour resection after chemotherapy (Rx), and at relapse (Rel), from 10 children uniformly treated for high-risk neuroblastoma, to define genes and pathways causing treatment resistance that may be therapeutically targeted.

Read the full summary ↓

Among transcriptomes from 26 samples containing 152,366 single cells, we identified 80,678 malignant sympathetic single cells. Patient-specific pseudotime and trajectory analyses of malignant cell responses to chemotherapy revealed some gene candidates such as STMN1 and ALYREF, upregulated in response to chemotherapy. Knockdown of these genes in human neuroblastoma cell lines sensitised cells to chemotherapy. Pathway-level analyses of cell trajectories highlighted Hedgehog signalling as a novel mechanism of chemoresistance, possibly emanating from tumour-resident Schwann cells. Hedgehog inhibitors restored sensitivity to chemotherapy in vitro and in vivo. The tumor microenvironment following chemotherapy identified enrichment of the pro-inflammatory proteoglycan serglycin (SRGN) as a novel immunotherapy target. Thus, a longitudinal single cell transcriptomic diagnostic of chemo-resistance in neuroblastoma can reveal therapeutic targets.

This dataset

Open GSE331214 in finder → Find more human RNA-seq datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE331214_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1467502. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 38 more — browse all 38 samples with per-sample file links →

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